A review of vibration-based gear wear monitoring and prediction techniques K Feng, JC Ji, Q Ni, M Beer Mechanical Systems and Signal Processing 182, 109605, 2023 | 164 | 2023 |
A fault information-guided variational mode decomposition (FIVMD) method for rolling element bearings diagnosis Q Ni, JC Ji, K Feng, B Halkon Mechanical Systems and Signal Processing 164, 108216, 2022 | 160 | 2022 |
Digital twin-driven intelligent assessment of gear surface degradation K Feng, JC Ji, Y Zhang, Q Ni, Z Liu, M Beer Mechanical Systems and Signal Processing 186, 109896, 2023 | 134 | 2023 |
Vibration-based updating of wear prediction for spur gears K Feng, P Borghesani, WA Smith, RB Randall, ZY Chin, J Ren, Z Peng Wear 426, 1410-1415, 2019 | 126 | 2019 |
A fault diagnosis method for planetary gearboxes under non-stationary working conditions using improved Vold-Kalman filter and multi-scale sample entropy Y Li, K Feng, X Liang, MJ Zuo Journal of Sound and Vibration 439, 271-286, 2019 | 112 | 2019 |
Physics-Informed LSTM hyperparameters selection for gearbox fault detection Y Chen, M Rao, K Feng, MJ Zuo Mechanical Systems and Signal Processing 171, 108907, 2022 | 101 | 2022 |
Use of cyclostationary properties of vibration signals to identify gear wear mechanisms and track wear evolution K Feng, WA Smith, P Borghesani, RB Randall, Z Peng Mechanical Systems and Signal Processing 150, 107258, 2021 | 92 | 2021 |
Data-driven prognostic scheme for bearings based on a novel health indicator and gated recurrent unit network Q Ni, JC Ji, K Feng IEEE Transactions on Industrial Informatics 19 (2), 1301-1311, 2022 | 91 | 2022 |
Vibration-based monitoring and prediction of surface profile change and pitting density in a spur gear wear process K Feng, WA Smith, RB Randall, H Wu, Z Peng Mechanical Systems and Signal Processing 165, 108319, 2022 | 75 | 2022 |
Digital twin-driven partial domain adaptation network for intelligent fault diagnosis of rolling bearing Y Zhang, JC Ji, Z Ren, Q Ni, F Gu, K Feng, K Yu, J Ge, Z Lei, Z Liu Reliability Engineering & System Safety 234, 109186, 2023 | 73 | 2023 |
A phase angle based diagnostic scheme to planetary gear faults diagnostics under non-stationary operational conditions K Feng, K Wang, Q Ni, MJ Zuo, D Wei Journal of Sound and Vibration 408, 190-209, 2017 | 67 | 2017 |
CFCNN: A novel convolutional fusion framework for collaborative fault identification of rotating machinery Y Xu, K Feng, X Yan, R Yan, Q Ni, B Sun, Z Lei, Y Zhang, Z Liu Information Fusion, 2023 | 60 | 2023 |
A novel correntropy-based band selection method for the fault diagnosis of bearings under fault-irrelevant impulsive and cyclostationary interferences Q Ni, JC Ji, K Feng, B Halkon Mechanical Systems and Signal Processing 153, 107498, 2021 | 60 | 2021 |
A novel vibration-based prognostic scheme for gear health management in surface wear progression of the intelligent manufacturing system K Feng, JC Ji, Q Ni, Y Li, W Mao, L Liu Wear, 204697, 2023 | 57 | 2023 |
Supervised contrastive learning-based domain adaptation network for intelligent unsupervised fault diagnosis of rolling bearing Y Zhang, Z Ren, S Zhou, K Feng, K Yu, Z Liu IEEE/ASME Transactions on Mechatronics 27 (6), 5371-5380, 2022 | 56 | 2022 |
An enhanced morphology gradient product filter for bearing fault detection Y Li, MJ Zuo, Y Chen, K Feng Mechanical Systems and Signal Processing 109, 166-184, 2018 | 54 | 2018 |
A diagnostic signal selection scheme for planetary gearbox vibration monitoring under non-stationary operational conditions K Feng, KS Wang, M Zhang, Q Ni, MJ Zuo Measurement Science and Technology 28 (3), 035003, 2017 | 53 | 2017 |
Physics-Informed Residual Network (PIResNet) for rolling element bearing fault diagnostics Q Ni, JC Ji, B Halkon, K Feng, AK Nandi Mechanical Systems and Signal Processing 200, 110544, 2023 | 49 | 2023 |
Universal source-free domain adaptation method for cross-domain fault diagnosis of machines Y Zhang, Z Ren, K Feng, K Yu, M Beer, Z Liu Mechanical Systems and Signal Processing 191, 2023 | 45 | 2023 |
Attention-based multiscale denoising residual convolutional neural networks for fault diagnosis of rotating machinery Y Xu, X Yan, K Feng, X Sheng, B Sun, Z Liu Reliability Engineering & System Safety 226, 108714, 2022 | 44 | 2022 |